Variant ranking pipeline for complex familial disorders

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Identifying genetic susceptibility factors for complex disorders is challenging due to genetic heterogeneity.
• Existing methods may not effectively analyze diverse pedigree collections (small and large).

Purpose of the Study:

• To develop and validate a novel computational pipeline, WARP, for prioritizing genetic variants and genes in complex disorders.
• To improve the identification of disease-associated genes across various family structures.

Main Methods:

• Developed the Weights-based vAriant Ranking in Pedigrees (WARP) pipeline.
• WARP utilizes five weighted factors: disease incidence, family case count, shared genome fraction, allele frequency, and variant deleteriousness.
• Variants are ranked using a multiplicative combination of weights, averaged across families to generate a multifamily weight.

Main Results:

• The WARP pipeline successfully identified known melanoma genes (POT1, MITF, BAP1) in 31% of familial melanoma cases studied.
• Analysis revealed potentially novel candidate genes for melanoma in the remaining families.
• The pipeline demonstrated effectiveness in prioritizing variants and genes for further investigation.

Conclusions:

• The WARP pipeline offers a robust approach for identifying disease-predisposing genes in studies involving both small and large pedigrees.
• This method enhances the ability to detect genetic factors in genetically heterogeneous complex disorders.
• WARP provides a valuable tool for genetic research and gene discovery in inherited diseases.